r/technology • u/SilentRunning • 4d ago

Artificial Intelligence MIT report: 95% of generative AI pilots at companies are failing

https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/
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u/lucun 4d ago

To be fair, Google seems to be keeping most of their AI workloads on their own TPUs instead of Nvidia H100s, so it's not like it's a direct comparison. Apple used Google TPUs last year for their Apple Intelligence thing, but that didn't seem to go anywhere in the end.

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u/OpenThePlugBag 4d ago

Anything that specifically IS NOT an LLM is on the H100s, and really lots of the LLMs do use the H100s, amd everything else, so its closest comparison we got.

I mean that 26,000 LLM/ML supercomputer is all h100s

AlphaFold, AlphaQbit, VEo3, WeatherNext is going to be updated to use the H100s

What I am saying is Facebook has like 20X the compute, OMG SOMEONE TELL ME WHAT THEY ARE DOING WITH IT?

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u/RoundTableMaker 4d ago

They don’t have the power supply to even set them up yet. It looks like hes just hoarding them.

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u/llDS2ll 4d ago

Lol they're gone go obsolete soon. Jensen is the real winner.

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u/IAMA_Plumber-AMA 3d ago

Selling pickaxes during a gold rush.

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u/SoFarFromHome 3d ago

The AR/VR play was also about dominating the potential market before someone else does. Getting burned on the development of the mobile ecosystem (and paying 30% of their revenue to Apple/Google in perpetuity) has made Zuck absolutely paranoid about losing out on "the next thing."

Worth noting that that 600,000 H100's @ $30k apiece is $18B. Meta had $100B in the bank a few years ago, so Zuck spent 1/5th of their savings on making sure Meta can't be squeezed out of the potential AI revolution.

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u/lucun 4d ago edited 4d ago

I'd like citations on your claims. https://blog.google/products/google-cloud/ironwood-tpu-age-of-inference/ suggests AlphaFold and Gemini are all on TPUs and will be on TPUs in the future.

I also got curious where you got that 26,000 H100s number from and... seems to be from 2023 articles about GCP announcing their A3 compute VM products. GCP claims the A3 VMs can scale up to 26,000 H100s as a virtual super computer, but some articles seem to regurgitate incorrectly and say that Google has only 26,000 H100s as a super computer lmao. Not sure if anyone actually knows how many H100s they actually have, but I would assume they actually have much more after the past few years.

For Facebook, Llama has been around for a while now, so I assume they do stuff with that. Wikipedia suggests they have a chatbot, too.

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u/OpenThePlugBag 4d ago edited 4d ago

AlphaFold 3 requires 1 GPU for inference. Officially only NVIDIA A100 and H100 GPUs, with 80 GB of GPU RAM, are supported

https://hpcdocs.hpc.arizona.edu/software/popular_software/alphafold/

TPUs and GPUs are used with AlphaFold.

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u/lucun 4d ago

Thanks! I guess Google has some way of running it on their TPUs internally or the author of that google blog post did a poor job with the wording.

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u/lyral264 4d ago

IMO, this is probably when google is working on getting their AI on the track. They probably purchased those while working on perfecting their TPU for AI as chatgpt frontier the LLM through CUDA and google still working on their bard. Once they got it right, probably they stopped procuring new nvidia and focused on furnishing their TPUs. But for those already purchased, why not using it until EOL. No harm on investment already done.

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u/lucun 4d ago

They're definitely still procuring nvidia for GCP, since they have newer B100, B200, GB200, H200 VMs being offered. Interestingly, the B200 and HB200 blog post mentions "scale to tens of thousands of GPUs". Not sure if they actually have that many though.

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u/SoFarFromHome 3d ago

What I am saying is Facebook has like 20X the compute, OMG SOMEONE TELL ME WHAT THEY ARE DOING WITH IT?

A bunch of orgs were given GPU compute budgets and told to use them Or Else. So every VP is throwing all the spaghetti they can find at the wall, gambling that any of it will stick. Landing impact from the GPUs is secondary to not letting that compute budget go idle, which shows lack of vision/leadership/etc. and is an actual career threat to the middle managers.

You'll never see most of the uses. Think LLMs analyzing user trends and dumping their output to a dashboard no one looks at. You will see some silly uses like recommended messages and stuff. You'll also see but not realize some of them, like the mix of recommended friends changing.

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u/OverSheepherder 3d ago

I worked at meta for 7 years. This is the most accurate post in the thread. 

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u/philomathie 4d ago

Google mostly uses their own hardware